Many supervised learning models pre-trained on large-scale datasets have been proposed mainly for SER tasks.
VGGish[1]} pre-trained on YouTube-8M[2]} is used as a feature extractor in various application studies[3]}[4]}[5]}[6]}[7]}.
Pre-trained Audio Neural Networks (PANNs)[8]} models pre-trained on AudioSet[9]} showed state-of-the-art results, and they have been used in application studies [10]}[7]}.
Pre-training on both ImageNet and AudioSet shows advantages: PSLA[12]}, ESResNe(X)t-fbsp[13]}, and Audio Spectrogram Transformer (AST)[14]} produced state-of-the-art results on SER.
